A new global tsunami exposure model for rapid post event assessment

Tools for tsunami impact analysis like USGS’s PAGER near-real-time impact assessments for earthquakes has been lacking within operational tsunami post-event assessments. Here, we introduce a new global model designed to estimate population exposure to tsunamis within minutes to hours after an event, supporting rapid post-event assessment developed within the ARISTOTLE-ENHSP. In a nutshell, the model combines model combines Tsunami-HySEA scenario simulations with Maximum Inundation Heights (MIHs) obtained by means of amplification factors and look up tables for population exposure. The method of amplification factors applies key wave parameters from Tsunami-HySEA, including offshore wave amplitude, period, and polarity, extracted through a dedicated time series analysis tool. To estimate inundated areas and human exposure, MIHs are extrapolated across a global digital elevation model (DEM) using a simplified bathtub-like friction-loss law. Pre-calculated inundation polygons, generated in discrete steps, enable rapid determination of affected regions. By overlaying these polygons with publicly available population datasets from the Global Human Settlement Layer (GHSL), the model produces exposure estimates within minutes to hours of an event. The approach prioritizes speed and global applicability over local precision; indeed, it does not incorporate high-resolution topography or detailed hydrodynamic simulations, and results carry significant uncertainty. However, this uncertainty is quantified based on the variability in inundation estimates and on bias offsets of the amplification factor approximation. A key focus of this presentation is to show selected comparisons with historical tsunami events, both towards inundation and exposure estimates. We finally discuss its intended role as a new supplement for providing rapid, approximate exposure estimates to inform post-event emergency response.